LLMs Should Decompose Long Tasks via Harness, Not Rely on Huge Context
CShorten30 · x · 2026-08-28
Yacine Learning argues against relying solely on massive context windows for LLMs to handle long tasks. Instead, models should manage context by decomposing difficult tasks through a 'harness' until manageable. Citing @a1zhang, the view is that Transformers struggle to generalize to untrained tasks, and it should be the harness's job to generalize through composition in 2026. Observations show that for tasks with shared structure, the root model naturally learns the same trajectory, implying the harness induces generalization rather than the model needing extra capabilities.
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